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CVPR
2009
IEEE
15 years 6 months ago
Higher-Order Clique Reduction in Binary Graph Cut
We introduce a new technique that can reduce any higher-order Markov random field with binary labels into a first-order one that has the same minima as the original. Moreover, w...
Hiroshi Ishikawa 0002
CVPR
2008
IEEE
15 years 1 months ago
Max Margin AND/OR Graph learning for parsing the human body
We present a novel structure learning method, Max Margin AND/OR Graph (MM-AOG), for parsing the human body into parts and recovering their poses. Our method represents the human b...
Long Zhu, Yuanhao Chen, Yifei Lu, Chenxi Lin, Alan...
ICML
2009
IEEE
14 years 12 months ago
Learning structurally consistent undirected probabilistic graphical models
In many real-world domains, undirected graphical models such as Markov random fields provide a more natural representation of the dependency structure than directed graphical mode...
Sushmita Roy, Terran Lane, Margaret Werner-Washbur...
CIKM
2008
Springer
14 years 1 months ago
Modeling multi-step relevance propagation for expert finding
An expert finding system allows a user to type a simple text query and retrieve names and contact information of individuals that possess the expertise expressed in the query. Thi...
Pavel Serdyukov, Henning Rode, Djoerd Hiemstra
MICCAI
2010
Springer
13 years 9 months ago
3D Knowledge-Based Segmentation Using Pose-Invariant Higher-Order Graphs
Segmentation is a fundamental problem in medical image analysis. The use of prior knowledge is often considered to address the ill-posedness of the process. Such a process consists...
Chaohui Wang, Olivier Teboul, Fabrice Michel, Salm...